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More mixed-integer linear programming models for solving three-stage remanufacturing system scheduling problem
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DOI：10.1016/j.cie.2024.110379.png)
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Abstract
En 中文
This paper aims to deal with the three-stage remanufacturing system scheduling problem (3T-RSSP) that minimizes the maximum completion time i.e., makespan. To this end, inspired by distinct modeling ideas, four mixedinteger linear programming (MILP) models are formulated. The modeling ideas used in this paper are sequencebased idea, position-based idea, time-based idea, and adjacent sequence-based idea. Numerical experiments are executed on a set of small-scaled, medium-scaled and large-scaled instances to test the performance of these formulated MILP models in terms of size complexity and computation complexity. Experimental results demonstrate that the sequence-based MILP model (Model 1) is the most efficient one while the time-based MILP model (Model 3) is worst one. The Wilcoxon signed-rank test is also conducted to evaluate the four models. Model 1 is further compared with different optimization solvers, heuristic and some state-of-art heuristics. Comparison results verify the effectiveness and good portability of the MILP model. Moreover, some key parameters contained in 3T-RSSP including end-of-life (EOL) products count, reprocessing lines count, disassembly workstations/reassembly workstations count are also evaluated. Notably, it is concluded that the increase of disassembly workstations/reassembly workstations count can improve the three-stage remanufacturing system's flexibility and contribute to the enhancement of production efficiency.
Keywords:
Three-stage remanufacturing system
scheduling
Makespan
Mixed-integer linear programming
Modeling and optimization
Journal
IF:
6.5
Papers:
1.0W
Citations:
3.8W
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